A stack of WNBA metrics that don't exist anywhere else. Each one was checked against what we know before it shipped: if a metric said a bench player out-impacted A'ja Wilson, we threw it out. The headline is the Auto Value Index (AVI), which blends six of them into one number. Any single metric moves a lot from one season to the next; the blend holds (year-over-year correlation +0.77, against under +0.2 for any one input).
Top 500 by projected minutes. Click any column header to sort; click a metric name to open its ranking page. Empty cells (—) mean the player didn't qualify under that metric's minimum-sample threshold.
Every Resolve WNBA advanced metric, with what it measures and how to read it. Each metric had to pass a face-validity gate before shipping — if a metric ranked someone obviously wrong, it got cut. Grouped by side (offense / defense / two-way / team).
How much opponents miss at the rim with this player on the floor.
What it measures: Opponent FG% at distance ≤5ft, on-vs-off court delta. Restricted to players with adequate rim attempts faced (≥100 on-court).
How to read it: Negative = elite (opponents shoot worse). 2026 leaders: Brittney Griner −0.118, Brianna Turner −0.113. Ezi Magbegor went from −0.147 in 2024 to +0.106 in 2025 and sits at +0.016 in 2026.
The headline number: six of our metrics blended into one.
What it measures: Composite value score combining O-RAPM, D-RAPM, NetRtg on-off, rim protection (RPV), usage and points per game into one number per player-season. Each input z-scored and weighted by √reliability, then scaled 0-100.
How to read it: 100 = league best, 50 = league average. A'ja Wilson 100.0 in 2024 and 2025; Breanna Stewart 100.0 in 2026, Wilson 91.5. YoY ρ=+0.759 — any single metric is noisy, the blend is not.
Ridge-regularized lineup impact per-100 possessions.
What it measures: Ridge α=300 regression of per-possession net rating on lineup membership. The standard 'impact' metric — McBride +7.15, Stewart +5.60, Wilson +4.24 lead the league.
How to read it: Per-100 net rating impact, pooled over 2024–2026 at α=300; ρ=+0.582 with raw NetRtg on-off. Veronica Burton leads at +7.52, Breanna Stewart +6.32.
Two-way star detector.
What it measures: Splits RAPM into separate offensive and defensive Ridge fits. Surfaces players who carry on both ends vs role specialists.
How to read it: Two-way stars: Veronica Burton (O+6.20 / D+5.76), Breanna Stewart (O+4.30 / D+5.32). Paige Bueckers is offense-first (O+6.04 / D+0.26). High on one only = specialist. Orthogonality ρ(O,D)=−0.052 confirms they're independent axes.
Raw on/off + the four shooting/turnover/free-throw decomposition.
What it measures: Net rating with player on vs off the floor, plus eFG/TOV%/FTr decomposition for both sides. The unregularized baseline RAPM is built against.
How to read it: Jackie Young's 2026 +21.53 on-off leads among players with 425+ possessions on court. ρ_eFG_Net=+0.618 confirms shooting dominates the four factors' contribution to net rating.
Which teammates' contributions rise together vs trade off.
What it measures: For each pair of teammates, the correlation of their per-game event shares when both are on the floor vs solo. Positive = activate together, negative = shift-share.
How to read it: Caitlin Clark's gravity surfaces here — Bonner-with-Clark coupling -0.099 means Bonner's share collapses when Clark plays. Negative coupling isn't bad — it's structural division of labor.
Last-5-min, score within 5 — net rating when it's on the line.
What it measures: On-court net rating restricted to clutch time (final 5 min, score margin ≤5). Volatile by design — clutch samples are small.
How to read it: ρ_clutch_vs_full=+0.012 — clutch is its own dimension, not a regular-time predictor. Among players with 100+ clutch possessions (2024–2026): Teaira McCowan +45.0, Allisha Gray +34.3, Courtney Williams +30.4. Use as a tiebreaker, not a primary metric.